Codestral 25.01 vs Qwen2.5-Coder-32B-Instruct: Who Codes Better?

Vipin Vashisth Last Updated : 03 Feb, 2025
13 min read

The emergence of advanced AI language models has transformed the programming landscape, setting new standards in coding efficiency and quality. Two coding models popular today are Mistral’s Codestral and Alibaba Cloud’s Qwen2.5-Coder – which this article will compare. In this comparison of Codestral 25.01 vs Qwen2.5-Coder-32B-Instruct, we will evaluate their coding capabilities to determine their best use cases.

Codestral 25.01 vs Qwen2.5-Coder-32B-Instruct: Overview

Qwen2.5-Coder-32B-Instruct, with its 32 billion parameters, is fine-tuned for coding tasks, delivering optimized, clear, and efficient solutions. Renowned for its precise instruction-following, Qwen is an excellent choice for developers seeking reliable and versatile code across various languages.

On the other hand, Codestral 25.01, with its robust 88 billion parameters, combines autoregressive modeling and reinforcement learning to tackle complex challenges. Its enterprise-focused features include superior security, compliance, and adaptability. These make Codestral a standout tool for coding, producing high-quality, error-free results.

Also Read: Qwen2.5-Max: ChatGPT’s Biggest Rival?

Codestral 25.01 vs Qwen2.5-Coder-32B-Instruct: Who Codes Better?

Codestral 25.01 vs Qwen2.5-Coder-32B-Instruct: Benchmark Comparison

In this section, we’ll see how these two models perform across various benchmarks.

Benchmark Codestral 25.01 Qwen2.5-Coder-32B-Instruct
HumanEval 86.6% 92.7%
MBPP 80.2% 90.2%
EvalPlusAverage 69.1% 86.3%
MultiPL-E Not available 79.4%
LiveCodeBench 37.9% 31.4%
CRUXEval 55.5% 83.4%
Aider Pass@2 Not available 73.7%
Spider 66.5% 85.1%

Sources:

Comparison Insights:

Qwen2.5-Coder-32B-Instruct excels in benchmarks that require structured task completion, such as HumanEval, MBPP, and Spider, making it an ideal choice for developers who prioritize accuracy and tackling technical challenges. On the other hand, Codestral 25.01 offers a balanced performance at a fraction of the cost, particularly shining in LiveCodeBench and SQL tasks like Spider. While it may not lead in HumanEval or MBPP benchmarks, its attractive cost-to-performance ratio makes it a compelling option for users who value efficiency and cost-effectiveness.

Also Read: Is Qwen2.5-Max Better than DeepSeek-R1 and Kimi k1.5?

Price Comparison:

Both Qwen2.5-Coder-32B-Instruct and Codestral 25.01 are cost-effective. Codestral 25.01 charges $0.30 for input and $0.90 for output per million tokens and Qwen2.5-Coder-32B-Instruct is an open-source model, you can check their pricing from here.

Codestral 25.01 vs Qwen2.5-Coder-32B-Instruct: Coding Capabilities

Now we will compare the programming capabilities of Codestral 25.01 and Qwen2.5-Coder-32B-Instruct. For that, we are going to give the same prompt to all models and evaluate their responses on the below metrics:

  1. Efficiency
  2. Readability
  3. Comment and Documentation
  4. Error Handling

Task1: Find Kth Largest Element

This problem challenges the model to use a more efficient approach compared to simpler methods like sorting.

Prompt: “Implement a C++ function that finds the Kth largest element in an unsorted array using the Quickselect algorithm. Ensure that the solution runs in average O(n) time complexity.”

Response by Qwen2.5-Coder-32B-Instruct

The Quickselect algorithm is an efficient selection algorithm to find the k-th smallest (or largest) element in an unordered list. It works by selecting a ‘pivot’ element from the array and partitioning the other elements into two sub-arrays until we have found our answer. Otherwise, we recursively apply the same logic to one of the sub-arrays. Here’s how you can implement this in C++:

#include <iostream>
#include <vector>
#include <algorithm> // For std::swap
// Function to partition the array around a pivot
int partition(std::vector<int>& nums, int left, int right) {
   int pivot = nums[right]; // Choose the last element as the pivot
   int i = left; // Index of the smaller element


   for (int j = left; j < right; ++j) {
       if (nums[j] > pivot) { // For Kth largest, use '>'
           std::swap(nums[i], nums[j]);
           ++i;
       }
   }
   std::swap(nums[i], nums[right]); // Place the pivot element at the correct position
   return i;
}
// Quickselect function to find the Kth largest element
int quickselect(std::vector<int>& nums, int left, int right, int k) {
   if (left == right) {
       return nums[left];
   }
   int pivotIndex = partition(nums, left, right);
   // If the pivot is in the correct position, return it
   if (k == pivotIndex) {
       return nums[k];
   }
   // If k is smaller than the pivot index, it must be in the left subarray
   else if (k < pivotIndex) {
       return quickselect(nums, left, pivotIndex - 1, k);
   }
   // If k is larger than the pivot index, it must be in the right subarray
   else {
       return quickselect(nums, pivotIndex + 1, right, k);
   }
}
// Wrapper function to find the Kth largest element
int findKthLargest(std::vector<int>& nums, int k) {
   int n = nums.size();
   // Convert k to zero-based index for the partitioning logic
   int kIndex = k - 1;
   return quickselect(nums, 0, n - 1, kIndex);
}
int main() {
   std::vector<int> nums = {3, 2, 1, 5, 6, 4,8};
   int k = 2;
   int kthLargest = findKthLargest(nums, k);
   std::cout << "The " << k << "th largest element is: " << kthLargest << std::endl;
   return 0;
}

Output of generated code:

"

Response by Codestral 25.01

Certainly! The Quickselect algorithm is a selection algorithm to find the k-th smallest element in an unordered list. It is related to the QuickSort sorting algorithm. Here is a C++ implementation of the Quickselect algorithm to find the Kth largest element in an unsorted array:

#include <iostream>
#include <vector>
#include <cstdlib>
#include <ctime>
// Function to partition the array on the basis of pivot element
int partition(std::vector<int>& arr, int low, int high) {
   int pivot = arr[high]; // Choosing the last element as pivot
   int i = low - 1; // Index of smaller element


   for (int j = low; j < high; j++) {
       if (arr[j] <= pivot) {
           i++;
           std::swap(arr[i], arr[j]);
       }
   }
   std::swap(arr[i + 1], arr[high]);
   return i + 1;
}
// Function to find the Kth largest element
int quickSelect(std::vector<int>& arr, int low, int high, int k) {
   if (low <= high) {
       int pivotIndex = partition(arr, low, high);


       if (pivotIndex == k) {
           return arr[pivotIndex];
       } else if (pivotIndex < k) {
           return quickSelect(arr, pivotIndex + 1, high, k);
       } else {
           return quickSelect(arr, low, pivotIndex - 1, k);
       }
   }
   return -1; // If k is out of bounds
}
// Function to find the Kth largest element in the array
int findKthLargest(std::vector<int>& arr, int k) {
   int n = arr.size();
   if (k > 0 && k <= n) {
       return quickSelect(arr, 0, n - 1, n - k);
   }
   return -1; // If k is out of bounds
}
int main() {
   std::vector<int> arr = {3, 2, 1, 5, 6, 4};
   int k = 2;
   int result = findKthLargest(arr, k);
   if (result != -1) {
       std::cout << "The " << k << "th largest element is " << result << std::endl;
   } else {
       std::cout << "Invalid value of k" << std::endl;
   }
   return 0;
}

Output of generated code:

"

Comparative Analysis

Qwen2.5-Coder-32B-Instruct offers an efficient, readable, and well-documented solution. Its clear structure and intuitive comments make it easy to understand, though it lacks robust error handling for edge cases.

Codestral 25.01 emphasizes error handling, with graceful checks for invalid inputs, but its generic implementation introduces unnecessary overhead. Readability is slightly compromised due to less intuitive naming and inconsistent comments.

Task 2: List Handling/Manipulation

This problem tests basic algorithmic skills, input validation, and error handling while remaining approachable to a broad audience.

Prompt: “Write a Java program that takes a list of integers and returns a new list containing only the prime numbers from the original list.”

Response by Qwen2.5-Coder-32B-Instruct

Certainly! Below is a Java program that takes a list of integers and returns a new list containing only the prime numbers from the original list.

import java.util.ArrayList;
import java.util.List;
public class PrimeNumberFilter {
   // Method to check if a number is prime
   public static boolean isPrime(int number) {
       if (number <= 1) {
           return false;
       }
       for (int i = 2; i <= Math.sqrt(number); i++) {
           if (number % i == 0) {
               return false;
           }
       }
       return true;
   }
   // Method to filter prime numbers from the list
   public static List<Integer> filterPrimeNumbers(List<Integer> numbers) {
       List<Integer> primeNumbers = new ArrayList<>();
       for (int number : numbers) {
           if (isPrime(number)) {
               primeNumbers.add(number);
           }
       }
       return primeNumbers;
   }
   public static void main(String[] args) {
       // Example usage
       List<Integer> numbers = new ArrayList<>();
       numbers.add(1);
       numbers.add(2);
       numbers.add(3);
       numbers.add(4);
       numbers.add(5);
       numbers.add(6);
       numbers.add(7);
       numbers.add(8);
       numbers.add(9);
       numbers.add(10);
       List<Integer> primeNumbers = filterPrimeNumbers(numbers);
       System.out.println("Prime numbers: " + primeNumbers);
   }
}

Output of generated code:

"

Response by Codestral 25.01

Here is a simple implementation of a rate limiter in Java. This implementation uses a sliding window algorithm to limit the number of requests per second.

import java.util.ArrayList;
import java.util.List;
public class PrimeNumberFilter {
   /**
    * Checks if a number is prime.
    *
    * @param number The number to check.
    * @return True if the number is prime, false otherwise.
    */
   public static boolean isPrime(int number) {
       if (number <= 1) {
           return false; // Numbers less than or equal to 1 are not prime
       }
       if (number <= 3) {
           return true; // 2 and 3 are prime numbers
       }
       if (number % 2 == 0 || number % 3 == 0) {
           return false; // Eliminate multiples of 2 and 3
       }
       for (int i = 5; i * i <= number; i += 6) {
           if (number % i == 0 || number % (i + 2) == 0) {
               return false; // Check divisibility by numbers of the form 6k ± 1
           }
       }
       return true;
   }
   /**
    * Filters a list of integers to return only the prime numbers.
    *
    * @param numbers The list of integers to filter.
    * @return A new list containing only the prime numbers from the original list.
    */
   public static List<Integer> filterPrimes(List<Integer> numbers) {
       List<Integer> primes = new ArrayList<>();
       for (int number : numbers) {
           if (isPrime(number)) {
               primes.add(number);
           }
       }
       return primes;
   }
   public static void main(String[] args) {
       // Example list of integers
       List<Integer> numbers = List.of(2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20);
       // Filter the list to get only prime numbers
       List<Integer> primeNumbers = filterPrimes(numbers);
       // Print the result
       System.out.println("Original list: " + numbers);
       System.out.println("Prime numbers: " + primeNumbers);
   }
}

Output of generated code:

"

Comparative Analysis

Qwen2.5-Coder-32B-Instruct provides a straightforward and efficient implementation. Its structure and variable names are clear, and the code is easy to follow. However, it lacks detailed comments and optimization in the prime-checking logic, which could improve performance for larger inputs.

Codestral 25.01 offers a more robust and optimized solution, leveraging advanced techniques like checking divisibility by 6k ± 1 numbers. It includes thorough documentation with detailed comments and well-structured methods. However, its verbosity might make it slightly harder to follow for beginners.

Task 3: String Manipulation

This problem focuses on string manipulation, error handling, and clear documentation.

Prompt: “Write a Python function that takes a string of digits and returns the sum of all the even digits”

Response by Qwen2.5-Coder-32B-Instruct

Certainly! Below is a Python function that takes a string of digits and returns the sum of all the even digits. The function also handles non-digit characters gracefully by raising a ValueError with an appropriate error message. The code is well-commented to explain the logic and purpose of each part.

def sum_of_even_digits(input_string: str) -> int:
   """
   Computes the sum of all even digits in the given string.
   :param input_string: A string containing digits.
   :return: The sum of all even digits in the string.
   :raises ValueError: If the input string contains non-digit characters.
   """
   # Initialize the sum of even digits to 0
   even_sum = 0
   # Iterate over each character in the input string
   for char in input_string:
       # Check if the character is a digit
       if char.isdigit():
           # Convert the character to an integer
           digit = int(char)
          
           # Check if the digit is even
           if digit % 2 == 0:
               # Add the even digit to the sum
               even_sum += digit
       else:
           # Raise a ValueError if the character is not a digit
           raise ValueError(f"Invalid character '{char}' found in input. Only digits are allowed.")
   # Return the sum of even digits
   return even_sum
# Example usage
try:
       input_string = "1234567890"
       result = sum_of_even_digits(input_string)
       print(f"The sum of even digits in '{input_string}' is: {result}")
      
       # Test with invalid input
       invalid_input = "123abc456"
       result = sum_of_even_digits(invalid_input)
       print(f"The sum of even digits in '{invalid_input}' is: {result}")
except ValueError as e:
       print(e)

Output of generated code:

"

Response by Codestral 25.01

Certainly! Below is a Python function that takes a string of digits, sums all the even digits, and handles non-digit characters gracefully. The function includes comments to explain the logic and error handling.

def sum_of_even_digits(digit_string):
   """
   Takes a string of digits and returns the sum of all the even digits.


   :param digit_string: A string containing digits.
   :return: The sum of all even digits in the string.
   :raises ValueError: If the input contains non-digit characters.
   """
   # Initialize the sum of even digits
   even_sum = 0
   # Iterate through each character in the input string
   for char in digit_string:
       # Check if the character is a digit
       if char.isdigit():
           # Convert the character to an integer
           digit = int(char)
           # Check if the digit is even
           if digit % 2 == 0:
               # Add the even digit to the sum
               even_sum += digit
       else:
           # Raise an error if a non-digit character is found
           raise ValueError(f"Invalid input: '{char}' is not a digit.")


   return even_sum
# Example usage
try:
   digit_string = "1234567890"
   result = sum_of_even_digits(digit_string)
   print(f"The sum of even digits in '{digit_string}' is: {result}")
except ValueError as e:
   print(e)
try:
   digit_string = "123a567890"
   result = sum_of_even_digits(digit_string)
   print(f"The sum of even digits in '{digit_string}' is: {result}")
except ValueError as e:
   print(e)

Output of generated code:

"

Comparative Analysis

Qwen2.5-Coder-32B-Instruct provides a well-structured and detailed implementation. It includes clear docstrings, robust error handling, and meaningful comments, making it easy to understand and maintain. Additionally, its example usage demonstrates both valid and invalid inputs, showcasing its error-handling capabilities.

Codestral 25.01 offers a functionally equivalent solution with similar robustness. However, its implementation is slightly less detailed in terms of comments and example usage, and its docstring is less descriptive compared to Qwen2.5-Coder-32B-Instruct.

Task 4: Error Handling

This problem evaluates the model’s ability to gracefully handle file errors, and invalid JSON data, and ensure the function provides useful feedback in case of failure.

Prompt: “Create a robust Python function that reads a JSON file, processes its contents, and returns a dictionary.”

You can find the JSON file we used for resting the code, here.

Response by Qwen2.5-Coder-32B-Instruct

Certainly! Below is a robust Python function that reads a JSON file, processes its contents, and returns a dictionary. The function handles various potential issues such as the file not being found, invalid JSON format, and incorrect structure. Detailed comments and documentation are provided to explain each part of the code.

import json
from typing import Dict, Any
import os
def read_and_process_json(file_path: str) -> Dict[str, Any]:
   """
   Reads a JSON file, processes its contents, and returns a dictionary.
   :param file_path: The path to the JSON file.
   :return: A dictionary containing the contents of the JSON file.
   :raises FileNotFoundError: If the file is not found.
   :raises json.JSONDecodeError: If the file contains invalid JSON.
   :raises ValueError: If the JSON structure is incorrect.
   """
   # Check if the file exists
   if not os.path.isfile(file_path):
       raise FileNotFoundError(f"The file '{file_path}' does not exist.")
   try:
       # Open and read the JSON file
       with open(file_path, 'r', encoding='utf-8') as file:
           data = json.load(file)
   except json.JSONDecodeError as e:
       raise json.JSONDecodeError(f"Invalid JSON format in file '{file_path}': {e}", e.doc, e.pos)
  
   # Validate the structure of the JSON data
   if not isinstance(data, dict):
       raise ValueError(f"Invalid JSON structure in file '{file_path}'. Expected a dictionary, got {type(data).__name__}.")


   return data
# Example usage
if __name__ == "__main__":
   try:
       file_path = "example.json"
       json_data = read_and_process_json(file_path)
       print("JSON Data:", json_data)
   except FileNotFoundError as e:
       print(e)
   except json.JSONDecodeError as e:
       print(e)
   except ValueError as e:
       print(e)

Output of generated code:

Codestral 25.01 vs Qwen2.5-Coder-32B-Instruct: Who Codes Better?

Response by Codestral 25.01

Certainly! Below is a Python function that reads a JSON file, processes its contents, and returns a dictionary. The function includes error handling for cases where the file is not found, the JSON is invalid, or the structure of the file is incorrect.

import json
import os


def read_json_file(file_path):
   """
   Reads a JSON file and returns its contents as a dictionary.
   :param file_path: The path to the JSON file.
   :return: A dictionary containing the JSON data.
   :raises FileNotFoundError: If the file is not found.
   :raises json.JSONDecodeError: If the JSON is invalid.
   :raises ValueError: If the structure of the file is incorrect.
   """
   try:
       # Check if the file exists
       if not os.path.isfile(file_path):
           raise FileNotFoundError(f"The file {file_path} does not exist.")
       # Open and read the JSON file
       with open(file_path, 'r') as file:
           data = json.load(file)
       # Check if the data is a dictionary
       if not isinstance(data, dict):
           raise ValueError("The JSON structure is incorrect. Expected a dictionary.")
       return data
   except FileNotFoundError as e:
       print(f"Error: {e}")
       return None
   except json.JSONDecodeError as e:
       print(f"Error: Invalid JSON. {e}")
       return None
   except ValueError as e:
       print(f"Error: {e}")
       return None


# Example usage
file_path = 'example.json'
json_data = read_json_file(file_path)
if json_data is not None:
   print("JSON data:", json_data)

Output of generated code:

"

Comparative Analysis

Qwen2.5-Coder-32B-Instruct delivers a robust and professional implementation with comprehensive error handling, detailed docstrings, and validation of JSON structure. Its separation of exceptions and descriptive error messages enhances usability and debugging. The function explicitly raises exceptions instead of suppressing errors, adhering to best practices for production-grade software.

Codestral 25.01 provides a simpler implementation that also handles key exceptions but lacks the clarity and separation offered by Qwen2.5-Coder-32B-Instruct. Errors are printed to the console and the function returns None, which is less explicit and may complicate error management in larger systems. Additionally, the docstring is concise but less descriptive.

Overall Summary

Task Qwen2.5-Coder-32B-Instruct Codestral 25.01
Find Kth Largest Element Efficient implementation and clear structure, but lacks robust error handling. Generic implementation with unnecessarily added overhead. Slightly less readable.
List Handling/Manipulation Simple and efficient prime number filter, but lacks optimization in the prime-checking logic. Optimized with advanced techniques like divisibility check. More detailed comments, but slightly verbose.
String Manipulation Well-documented function with robust error handling and meaningful comments. Functionally equivalent but slightly less detailed in comments and example usage.
Error Handling Explicit error handling and production-friendly code make it better for practical uses. Less detailed documentation and less structured approach reduces its suitability for error handling in practical or learning contexts.

Conclusion

As we have seen in this article, both Qwen2.5-Coder-32B-Instruct and Codestral 25.01 have their own strengths and weaknesses. Qwen2.5-Coder-32B-Instruct excels in error handling, clarity, and comprehensive documentation, making it the preferred choice for reliability and best practices. Codestral 25.01, while efficient and functional, falls short in robustness and depth, limiting its suitability for production-grade use. With targeted improvements, Codestral 25.01 could enhance its appeal, but for now, Qwen2.5-Coder-32B-Instruct remains the superior option for demanding scenarios.

Frequently Asked Questions

Q1. What are the key differences between Codestral 25.01 and Qwen2.5-Coder-32B-Instruct in terms of error handling?

A. Qwen2.5-Coder-32B-Instruct raises explicit exceptions, such as FileNotFoundError and ValueError, providing clear error messages that help with debugging. In contrast, Codestral 25.01 prints error messages and returns None for error cases, which can be less informative and harder to manage in larger systems.

Q2. Which model is better for production environments: Codestral 25.01 or Qwen2.5-Coder-32B-Instruct?

A. Qwen2.5-Coder-32B-Instruct is better suited for production environments due to its robust error handling, detailed documentation, and adherence to best practices. Codestral 25.01 is efficient but lacks explicit exception handling and comprehensive documentation, which could lead to potential issues in production.

Q3. How do the documentation and comments compare between Codestral 25.01 and Qwen2.5-Coder-32B-Instruct?

A. Qwen2.5-Coder-32B-Instruct offers more detailed documentation and well-structured comments, making it easier for users to understand the code and its functionality. Codestral 25.01 provides concise documentation but lacks the depth of explanation found in Qwen2.5-Coder-32B-Instruct, potentially making it harder for users to grasp the code’s nuances.

Q4. Is Codestral 25.01 more efficient than Qwen2.5-Coder-32B-Instruct?

A. Both Codestral 25.01 and Qwen2.5-Coder-32B-Instruct are efficient in their respective implementations. However, Qwen2.5-Coder-32B-Instruct is more optimized in terms of error management and modularity, which can enhance long-term efficiency in complex projects. Codestral 25.01 may be faster in some cases but is less robust in error handling.

Q5. Which model is better for educational purposes: Codestral 25.01 or Qwen2.5-Coder-32B-Instruct?

A. Qwen2.5-Coder-32B-Instruct is better for educational purposes due to its clear documentation, well-commented code, and structured approach to error handling. It serves as a great learning resource for those looking to understand best practices in coding and error management. Codestral 25.01, while functional, lacks the same level of clarity and detail in its explanations.

Hello! I'm Vipin, a passionate data science and machine learning enthusiast with a strong foundation in data analysis, machine learning algorithms, and programming. I have hands-on experience in building models, managing messy data, and solving real-world problems. My goal is to apply data-driven insights to create practical solutions that drive results. I'm eager to contribute my skills in a collaborative environment while continuing to learn and grow in the fields of Data Science, Machine Learning, and NLP.

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